Semantic Web 2010 Technical Workshop

Semantic Web Workshop

   * Semantic Web - Three part presentation 
   * Peter Fox, Rahul Ramachandran, Hook Hua

Lecture 1: Practical aspects of creating semantic web applications by Peter Fox

This part of the workshop is targeted at audience that spans the mid-advanced beginner to intermediate level interested in what an initial end-to-end prototype implementation of a semantic web application would consist of. The presentation will start with a use case, decompose it along with needed vocabularies, and relationships, perform the initial modeling, reuse and engineering steps for the ontology, using tools such as Cmap and Protege and proceed to instance generation, ontology validation and verification, prototyping triple store, query and programming language and inference choices that may need to be made. The participant should come away with the general method and suitable initial prototyping choices that can be made when starting semantic web applications so that long development cycles are minimized.

Lecture 2: Building a Linked Data Cloud for Earth Science by Rahul Ramachandran

Semantic Web isn’t just about putting data on the web. It is about making links so that a person or machine can explore the web of data. With linked data, when you have some of it, you can find other, related data" - Tim Berners-Lee.

This presentation will look at what is linked data? How to publish and consume data in this cloud? Some existing examples and research applications will be presented. Finally, this presentation will focus on Earth Science specific issues related to Linked Data such as existing technology components and hurdles.

Lecture 3: Semantic Web Technologies for Addressing Knowledge Gaps in Using Science Applications by Hook Hua

Many science data processing suites have grown in complexity where no single person may fully understand all aspects of the system. Developed over the course of years (or decades) and by many groups of people, these processing software often encompass a plethora of processing steps and data products. We will present an overview of various semantically-driven technologies and techniques that can address this knowledge gap issue in the scope of InSAR data processing. We will cover ontology development and how it can be applied with inferencing, rules, query, and natural language processing to help the non-expert users.